12 citations · 12 across the 4 of their papers we have counts for
4 papers
Block Circulant Adapter for Large Language Models
Xinyu Ding, Meiqi Wang, Siyu Liao +1
Fine-tuning large language models (LLMs) is difficult due to their huge model size. Recent Fourier domain-based methods show potential for reducing fine-tuning costs. We propose a…
Elbert: Fast Albert with Confidence-Window Based Early Exit
Keli Xie, Siyuan Lu, Meiqi Wang +1
Despite the great success in Natural Language Processing (NLP) area, large pre-trained language models like BERT are not well-suited for resource-constrained or real-time applicati…
Transform-Based Feature Map Compression for CNN Inference
Yubo Shi, Meiqi Wang, Siyi Chen +2
To achieve higher accuracy in machine learning tasks, very deep convolutional neural networks (CNNs) are designed recently. However, the large memory access of deep CNNs will lead…
Hardware Accelerator for Multi-Head Attention and Position-Wise Feed-Forward in the Transformer
Siyuan Lu, Meiqi Wang, Shuang Liang +2
Designing hardware accelerators for deep neural networks (DNNs) has been much desired. Nonetheless, most of these existing accelerators are built for either convolutional neural ne…